Modelling and optimization of residual stress induction on laser-worked X12Cr turbine blades

Year 2023, Volume: 7 Issue: 3, 257 - 268, 30.09.2023

Festus Oluwadare Fameso , Dawood Desai Schalk Kok Dylan Armfield Mark Newby

https://doi.org/10.30521/jes.1249912

Abstract

The energy and power industry conventionally depends on large-scale turbomachinery to meet the ever-growing global energy demands. However, unplanned in-service failures remain a threat to sustainability with safety and economic consequences. The laser shock surface treatment technique is being considered a competitive alternative in mitigating crack initiation and growth, wear and fatigue of industrial components such as turbine blades. This paper presents the modelling and optimization of laser shock treatment parameters using numerical methods and commercial codes such as ABAQUS® and MATLAB®. Model-based process optimization parameters for the induction of global optimum compressive residual stress distribution in laser-worked Chromium-12 based high strength steel alloy (X12Cr) turbine blade is established, showing parametric combinations of inputs variables within the domain under investigation, yielding maximized CRS outputs. A hierarchy of significance of the input parameters to the laser shock peening process for stress induction has also been put forward as an outcome of this study. The capacity to predict and analyze outcomes before actual treatment of the components is beneficial and imperative to cutting costs, downtimes and other economic losses associated with unplanned failure of these components.

Keywords

Failure, Laser shock peening, Modelling, Residual stresses, Optimization

Supporting Institution

South Africa National Research Foundation (NRF)

Project Number

NRF Grant Reference No: SFH170720255948

Thanks

The authors would like to recognize the contribution of the National Research Foundation (NRF Grant Reference No: SFH170720255948), the National Laser Centre, Centre for Scientific and Industrial Research, Pretoria, Tshwane University of Technology, Eskom Holdings (SOC) Ltd, and the Department of Science and Innovation (DSI), all in the Republic of South Africa, in terms of financial and technical support of towards the success of this study. The opinions presented and conclusions inferred thereof are those of the author(s) and are not to be attributed to the NRF, Eskom Holdings or the DSI.

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